Neurobiology of DiseaseNeurosciencePeer-reviewed journal article
Cellular- and systems-level profiling of amyloid-beta effects on circadian timing
Kari R. HoytiD, Tyler A Kyhl, Nicklaus R. HalloyiD, Karl H. ObrietaniD
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Abstract
Disruption of the circadian timing system has been reported in the preclinical phase of Alzheimers disease (AD) and is a well-characterized component of mid- and late-stage AD. Given the distributed nature of the circadian timing system, with a central pacemaker in the suprachiasmatic nucleus (SCN) and peripheral clocks throughout the brain, understanding how AD affects this system has been challenging. To investigate how AD may disrupt circadian physiology, we focused on the amyloid-beta peptide, a key contributor to familial early-onset AD. Using the 5xFAD mouse model and ex vivo single-cell profiling, we examined how amyloid-beta influences clock timing in both SCN neurons and hippocampal neuronal populations. Circadian profiling of 5xFAD mice (4-and 8-months-old) showed only modest changes in key clock timing properties, including a shortening of the SCN rhythm. Interestingly, the mice showed enhanced rates of re-entrainment to changes in the light cycle, suggesting that elevated amyloid-beta levels increase the sensitivity of the SCN clock to light. Further, using both in vitro SCN slice explant and dispersed SCN culture models, the exogenous administration of oligomerized amyloid-beta had no significant effect on inherent clock timing capacity. In contrast, the timing properties of cultured hippocampal neurons showed a dose-dependent sensitivity to amyloid-beta. This included an elevated mesor and an increased rhythm amplitude. These findings reveal a divergence in amyloid-beta sensitivity between the central SCN clock and peripheral oscillators. This raises the possibility that circadian disruptions in AD may stem from both the destabilization and decoupling of peripheral oscillators from the central timing properties of the SCN.
- organism: mouse
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- approach: statistical model
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